| # | |
| # Pyserini: Reproducible IR research with sparse and dense representations | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # | |
| import json | |
| from pyserini.encode import QueryEncoder | |
| class CachedDataQueryEncoder(QueryEncoder): | |
| def __init__(self, model_name_or_path): | |
| self.vectors = self._load_from_jsonl(model_name_or_path) | |
| def _load_from_jsonl(path): | |
| vectors = {} | |
| with open(path) as f: | |
| for line in f: | |
| info = json.loads(line) | |
| text = info['contents'].strip() | |
| vec = info['vector'] | |
| vectors[text] = vec | |
| return vectors | |
| def encode(self, text, **kwargs): | |
| return self.vectors[text.strip()] | |